@article{GuentherSchueleZurelletal.2023, author = {G{\"u}nther, Oliver and Sch{\"u}le, Manja and Zurell, Damaris and Jeltsch, Florian and Roeleke, Manuel and Kampe, Heike and Zimmermann, Matthias and Scholz, Jana and Engbert, Ralf and Elsner, Birgit and Schlangen, David and Agrofylax, Luisa and Georgi, Doreen and Weymar, Mathias and Wagener, Thorsten and Bookhagen, Bodo and Eibl, Eva P. S. and Korup, Oliver and Oswald, Sascha Eric and Thieken, Annegret and van der Beek, Peter}, title = {Portal Wissen = Exzellenz}, series = {Portal Wissen: Das Forschungsmagazin der Universit{\"a}t Potsdam}, journal = {Portal Wissen: Das Forschungsmagazin der Universit{\"a}t Potsdam}, number = {02/2023}, issn = {2194-4245}, doi = {10.25932/publishup-61144}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-611440}, pages = {98}, year = {2023}, abstract = {Was nicht nur gut oder sehr gut ist, nennen wir gern exzellent. Aber was meint das eigentlich? Vom lateinischen „excellere" kommend, beschreibt es Dinge, Personen oder Handlungen, die „hervor-" oder „herausragen" aus der Menge, sich „auszeichnen" gegen{\"u}ber anderen. Mehr geht nicht. Exzellenz ist das Mittel der Wahl, wenn es darum geht, der Erste oder Beste zu sein. Und das macht auch vor der Forschung nicht halt. Wer auf die Universit{\"a}t Potsdam schaut, findet zahlreiche ausgezeichnete Forschende, hervorragende Projekte und immer wieder auch aufsehenerregende Erkenntnisse, Ver{\"o}ffentlichungen und Ergebnisse. Aber ist die UP auch exzellent? Eine Frage, die 2023 ganz sicher andere Wellen schl{\"a}gt als vielleicht vor 20 Jahren. Denn seit dem Start der Exzellenzinitiative 2005 gelten als - w{\"o}rtlich - exzellent jene Hochschulen, denen es gelingt, in dem umfangreichsten F{\"o}rderprogramm f{\"u}r Wissenschaft in Deutschland einen Zuschlag zu erhalten. Egal ob in Form von Graduiertenschulen, Forschungsclustern oder - seit Fortsetzung des Programms ab 2019 unter dem Titel „Exzellenzstrategie" - ganzen Exzellenzuniversit{\"a}ten: Wer im Kreis der Forschungsuniversit{\"a}ten zu den Besten geh{\"o}ren will, braucht das Siegel der Exzellenz. In der gerade eingel{\"a}uteten neuen Wettbewerbsrunde der „Exzellenzstrategie des Bundes und der L{\"a}nder" bewirbt sich die Universit{\"a}t Potsdam mit drei Clusterskizzen um F{\"o}rderung. Ein Antrag kommt aus der {\"O}kologie- und Biodiversit{\"a}tsforschung. Ziel ist es, ein komplexes Bild {\"o}kologischer Prozesse zu zeichnen - und dabei die Rolle von einzelnen Individuen ebenso zu betrachten wie das Zusammenwirken vieler Arten in einem {\"O}kosystem, um die Funktion der Artenvielfalt genauer zu bestimmen. Eine zweite Skizze haben die Kognitionswissenschaften eingereicht. Hier soll das komplexe Nebeneinander von Sprache und Kognition, Entwicklung und Lernen sowie Motivation und Verhalten als dynamisches Miteinander erforscht werden - wobei auch mit den Erziehungswissenschaften kooperiert wird, um verkn{\"u}pfte Lernund Bildungsprozesse stets mitzudenken. Der dritte Antrag aus den Geo- und Umweltwissenschaften nimmt extreme und besonders folgenschwere Naturgefahren und -prozesse wie {\"U}berschwemmungen und D{\"u}rren in den Blick. Die Forschenden untersuchen die Extremereignisse mit besonderem Fokus auf deren Wechselwirkung mit der Gesellschaft, um mit ihnen einhergehende Risiken und Sch{\"a}den besser einsch{\"a}tzen sowie k{\"u}nftig rechtzeitig Maßnahmen einleiten zu k{\"o}nnen. „Alle drei Antr{\"a}ge zeichnen ein hervorragendes Bild unserer Leistungsf{\"a}higkeit", betont der Pr{\"a}sident der Universit{\"a}t, Prof. Oliver G{\"u}nther, Ph.D. „Die Skizzen dokumentieren eindrucksvoll unser Engagement, vorhandene Forschungsexzellenz sowie die Potenziale der Universit{\"a}t Potsdam insgesamt. Allein die Tatsache, dass sich drei schlagkr{\"a}ftige Konsortien in ganz unterschiedlichen Themenbereichen zusammengefunden haben, zeigt, dass wir auf unserem Weg in die Spitzengruppe der deutschen Universit{\"a}ten einen guten Schritt vorangekommen sind." In diesem Heft schauen wir, was sich in und hinter diesen Antr{\"a}gen verbirgt: Wir haben mit den Wissenschaftlerinnen und Wissenschaftlern gesprochen, die sie geschrieben haben, und sie gefragt, was sie sich vornehmen, sollten sie den Zuschlag erhalten und ein Cluster an die Universit{\"a}t holen. Wir haben aber auch auf die Forschung geschaut, die zu den Antr{\"a}gen gef{\"u}hrt hat und die schon l{\"a}nger das Profil der Universit{\"a}t pr{\"a}gt und ihr national wie international Anerkennung eingebracht hat. Wir stellen eine kleine Auswahl an Projekten, Methoden und Forschenden vor, um zu zeigen, warum in diesen Antr{\"a}gen tats{\"a}chlich exzellente Forschung steckt! {\"U}brigens: Auch „Exzellenz" ist nicht das Ende der Fahnenstange. Immerhin l{\"a}sst sich das Adjektiv exzellent sogar steigern. In diesem Sinne w{\"u}nschen wir exzellentestes Vergn{\"u}gen beim Lesen!}, language = {de} } @article{GuentherSchueleZurelletal.2023, author = {G{\"u}nther, Oliver and Sch{\"u}le, Manja and Zurell, Damaris and Jeltsch, Florian and Roeleke, Manuel and Kampe, Heike and Zimmermann, Matthias and Scholz, Jana and Mikulla, Stefanie and Engbert, Ralf and Elsner, Birgit and Schlangen, David and Agrofylax, Luisa and Georgi, Doreen and Weymar, Mathias and Wagener, Thorsten and Bookhagen, Bodo and Eibl, Eva P. S. and Korup, Oliver and Oswald, Sascha Eric and Thieken, Annegret and van der Beek, Peter}, title = {Portal Wissen = Excellence}, series = {Portal Wissen: The research magazine of the University of Potsdam}, journal = {Portal Wissen: The research magazine of the University of Potsdam}, number = {02/2023}, issn = {2198-9974}, doi = {10.25932/publishup-61145}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-611456}, pages = {58}, year = {2023}, abstract = {When something is not just good or very good, we often call it excellent. But what does that really mean? Coming from the Latin word "excellere," it describes things, persons, or actions that are outstanding or superior and distinguish themselves from others. It cannot get any better. Excellence is the top choice for being the first or the best. Research is no exception. At the university, you will find numerous exceptional researchers, outstanding projects, and, time and again, sensational findings, publications, and results. But is the University of Potsdam also excellent? A question that will certainly create a different stir in 2023 than it did perhaps 20 years ago. Since the launch of the Excellence Initiative in 2005, universities that succeed in winning the most comprehensive funding program for research in Germany have been considered - literally - excellent. Whether in the form of graduate schools, research clusters, or - since the program was continued in 2019 under the title "Excellence Strategy" - entire universities of excellence: Anyone who wants to be among the best research universities needs the seal of excellence. The University of Potsdam is applying for funding with three cluster proposals in the recently launched new round of the "Excellence Strategy of the German Federal and State Governments." One proposal comes from ecology and biodiversity research. The aim is to paint a comprehensive picture of ecological processes by examining the role of single individuals as well as the interactions among many species in an ecosystem to precisely determine the function of biodiversity. A second proposal has been submitted by the cognitive sciences. Here, the complex coexistence of language and cognition, development and learning, as well as motivation and behavior will be researched as a dynamic interrelation. The projects will include cooperation with the educational sciences to constantly consider linked learning and educational processes. The third proposal from the geo and environmental sciences concentrates on extreme and particularly devastating natural hazards and processes such as floods and droughts. The researchers examine these extreme events, focusing on their interaction with society, to be able to better assess the risks and damages they might involve and to initiate timely measures in the future. "All three proposals highlight the excellence of our performance," emphasizes University President Prof. Oliver G{\"u}nther, Ph.D. "The outlines impressively document our commitment, existing research excellence, and the potential of the University of Potsdam as a whole. The fact that three powerful consortia have come together in different subject areas shows that we have taken a good step forward on our way to becoming one of the top German universities." In this issue, we are looking at what is in and behind these proposals: We talked to the researchers who wrote them. We asked them about their plans in case their proposals are successful and they bring a cluster of excellence to the university. But we also looked at the research that has led to the proposals, has long shaped the university's profile, and earned it national and international recognition. We present a small selection of projects, methods, and researchers to illustrate why there really is excellent research in these proposals! By the way, "excellence" is also not the end of the flagpole. After all, the adjective "excellent" even has a comparative and a superlative. With this in mind, I wish you the most excellent pleasure reading this issue!}, language = {en} } @article{ZurellKoenigMalchowetal.2022, author = {Zurell, Damaris and K{\"o}nig, Christian and Malchow, Anne-Kathleen and Kapitza, Simon and Bocedi, Greta and Travis, Justin M. J. and Fandos, Guillermo}, title = {Spatially explicit models for decision-making in animal conservation and restoration}, series = {Ecography : pattern and diversity in ecology / Nordic Ecologic Society Oikos}, journal = {Ecography : pattern and diversity in ecology / Nordic Ecologic Society Oikos}, number = {4}, publisher = {Wiley-Blackwell}, address = {Oxford}, issn = {1600-0587}, doi = {10.1111/ecog.05787}, pages = {1 -- 16}, year = {2022}, abstract = {Models are useful tools for understanding and predicting ecological patterns and processes. Under ongoing climate and biodiversity change, they can greatly facilitate decision-making in conservation and restoration and help designing adequate management strategies for an uncertain future. Here, we review the use of spatially explicit models for decision support and to identify key gaps in current modelling in conservation and restoration. Of 650 reviewed publications, 217 publications had a clear management application and were included in our quantitative analyses. Overall, modelling studies were biased towards static models (79\%), towards the species and population level (80\%) and towards conservation (rather than restoration) applications (71\%). Correlative niche models were the most widely used model type. Dynamic models as well as the gene-to-individual level and the community-to-ecosystem level were underrepresented, and explicit cost optimisation approaches were only used in 10\% of the studies. We present a new model typology for selecting models for animal conservation and restoration, characterising model types according to organisational levels, biological processes of interest and desired management applications. This typology will help to more closely link models to management goals. Additionally, future efforts need to overcome important challenges related to data integration, model integration and decision-making. We conclude with five key recommendations, suggesting that wider usage of spatially explicit models for decision support can be achieved by 1) developing a toolbox with multiple, easier-to-use methods, 2) improving calibration and validation of dynamic modelling approaches and 3) developing best-practise guidelines for applying these models. Further, more robust decision-making can be achieved by 4) combining multiple modelling approaches to assess uncertainty, and 5) placing models at the core of adaptive management. These efforts must be accompanied by long-term funding for modelling and monitoring, and improved communication between research and practise to ensure optimal conservation and restoration outcomes.}, language = {en} } @article{MalchowBocediPalmeretal.2021, author = {Malchow, Anne-Kathleen and Bocedi, Greta and Palmer, Stephen C. F. and Travis, Justin M. J. and Zurell, Damaris}, title = {RangeShiftR: an R package for individual-based simulation of spatial eco-evolutionary dynamics and speciesu0027 responses to environmental changes}, series = {Ecography}, volume = {44}, journal = {Ecography}, number = {10}, publisher = {John Wiley \& Sons, Inc.}, address = {New Jersey}, issn = {1600-0587}, pages = {10}, year = {2021}, abstract = {Reliably modelling the demographic and distributional responses of a species to environmental changes can be crucial for successful conservation and management planning. Process-based models have the potential to achieve this goal, but so far they remain underused for predictions of species' distributions. Individual-based models offer the additional capability to model inter-individual variation and evolutionary dynamics and thus capture adaptive responses to environmental change. We present RangeShiftR, an R implementation of a flexible individual-based modelling platform which simulates eco-evolutionary dynamics in a spatially explicit way. The package provides flexible and fast simulations by making the software RangeShifter available for the widely used statistical programming platform R. The package features additional auxiliary functions to support model specification and analysis of results. We provide an outline of the package's functionality, describe the underlying model structure with its main components and present a short example. RangeShiftR offers substantial model complexity, especially for the demographic and dispersal processes. It comes with elaborate tutorials and comprehensive documentation to facilitate learning the software and provide help at all levels. As the core code is implemented in C++, the computations are fast. The complete source code is published under a public licence, making adaptations and contributions feasible. The RangeShiftR package facilitates the application of individual-based and mechanistic modelling to eco-evolutionary questions by operating a flexible and powerful simulation model from R. It allows effortless interoperation with existing packages to create streamlined workflows that can include data preparation, integrated model specification and results analysis. Moreover, the implementation in R strengthens the potential for coupling RangeShiftR with other models.}, language = {en} } @misc{MalchowBocediPalmeretal.2021, author = {Malchow, Anne-Kathleen and Bocedi, Greta and Palmer, Stephen C. F. and Travis, Justin M. J. and Zurell, Damaris}, title = {RangeShiftR: an R package for individual-based simulation of spatial eco-evolutionary dynamics and speciesu0027 responses to environmental changes}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {10}, issn = {1866-8372}, doi = {10.25932/publishup-52397}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-523979}, pages = {12}, year = {2021}, abstract = {Reliably modelling the demographic and distributional responses of a species to environmental changes can be crucial for successful conservation and management planning. Process-based models have the potential to achieve this goal, but so far they remain underused for predictions of species' distributions. Individual-based models offer the additional capability to model inter-individual variation and evolutionary dynamics and thus capture adaptive responses to environmental change. We present RangeShiftR, an R implementation of a flexible individual-based modelling platform which simulates eco-evolutionary dynamics in a spatially explicit way. The package provides flexible and fast simulations by making the software RangeShifter available for the widely used statistical programming platform R. The package features additional auxiliary functions to support model specification and analysis of results. We provide an outline of the package's functionality, describe the underlying model structure with its main components and present a short example. RangeShiftR offers substantial model complexity, especially for the demographic and dispersal processes. It comes with elaborate tutorials and comprehensive documentation to facilitate learning the software and provide help at all levels. As the core code is implemented in C++, the computations are fast. The complete source code is published under a public licence, making adaptations and contributions feasible. The RangeShiftR package facilitates the application of individual-based and mechanistic modelling to eco-evolutionary questions by operating a flexible and powerful simulation model from R. It allows effortless interoperation with existing packages to create streamlined workflows that can include data preparation, integrated model specification and results analysis. Moreover, the implementation in R strengthens the potential for coupling RangeShiftR with other models.}, language = {en} } @article{deOliveiraSilvaPiratelliZurelletal.2021, author = {de Oliveira-Silva, Anna Elizabeth and Piratelli, Augusto Jo{\~a}o and Zurell, Damaris and da Silva, Fernando Rodrigues}, title = {Vegetation cover restricts habitat suitability predictions of endemic Brazilian Atlantic Forest birds}, series = {Perspectives in Ecology and Conservation}, volume = {20}, journal = {Perspectives in Ecology and Conservation}, number = {1}, publisher = {Elsevier}, address = {Oxford}, issn = {2530-0644}, doi = {10.1016/j.pecon.2021.09.002}, pages = {1 -- 8}, year = {2021}, abstract = {Ecological niche models (ENMs) are often used to investigate how climatic variables from known occurrence records can estimate potential species range distribution. Although climate-based ENMs provide critical baseline information, the inclusion of non-climatic predictors related to vegetation cover might generate more realistic scenarios. This assumption is particularly relevant for species with life-history traits related to forest habitats and sensitive to habitat loss and fragmentation. Here, we developed ENMs for 36 Atlantic Forest endemic birds considering two sets of predictor variables: (i) climatic variables only and (ii) climatic variables combined with the percentage of remaining native vegetation. We hypothesized that the inclusion of native vegetation data would decrease the potential range distribution of forest-dependent species by limiting their occurrence in regions harboring small areas of native vegetation habitats, despite otherwise favorable climatic conditions. We also expected that habitat restriction in the climate-vegetation models would be more pronounced for highly forest-dependent birds. The inclusion of vegetation data in the modeling procedures restricted the final distribution ranges of 22 out of 36 modeled species, while the 14 remaining presented an expansion of their ranges. We observed that species with high and medium forest dependency showed higher restriction in range size predictions between predictor sets than species with low forest dependency, which showed no alteration or range expansion. Overall, our results suggest that ENMs based on climatic and landscape variables may be a useful tool for conservationists to better understand the dynamic of bird species distributions in threatened and highly fragmented regions such as the Atlantic Forest hotspot.(c) 2021 Associacao Brasileira de Cie circumflex accent ncia Ecol ogica e Conservacao. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/ ).}, language = {en} } @misc{ZurellKoenigMalchowetal.2021, author = {Zurell, Damaris and K{\"o}nig, Christian and Malchow, Anne-Kathleen and Kapitza, Simon and Bocedi, Greta and Travis, Justin M. J. and Fandos, Guillermo}, title = {Spatially explicit models for decision-making in animal conservation and restoration}, series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, volume = {2022}, journal = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, edition = {4}, publisher = {Universit{\"a}tsverlag Potsdam}, address = {Potsdam}, issn = {1866-8372}, doi = {10.25932/publishup-54991}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-549915}, pages = {1 -- 16}, year = {2021}, abstract = {Models are useful tools for understanding and predicting ecological patterns and processes. Under ongoing climate and biodiversity change, they can greatly facilitate decision-making in conservation and restoration and help designing adequate management strategies for an uncertain future. Here, we review the use of spatially explicit models for decision support and to identify key gaps in current modelling in conservation and restoration. Of 650 reviewed publications, 217 publications had a clear management application and were included in our quantitative analyses. Overall, modelling studies were biased towards static models (79\%), towards the species and population level (80\%) and towards conservation (rather than restoration) applications (71\%). Correlative niche models were the most widely used model type. Dynamic models as well as the gene-to-individual level and the community-to-ecosystem level were underrepresented, and explicit cost optimisation approaches were only used in 10\% of the studies. We present a new model typology for selecting models for animal conservation and restoration, characterising model types according to organisational levels, biological processes of interest and desired management applications. This typology will help to more closely link models to management goals. Additionally, future efforts need to overcome important challenges related to data integration, model integration and decision-making. We conclude with five key recommendations, suggesting that wider usage of spatially explicit models for decision support can be achieved by 1) developing a toolbox with multiple, easier-to-use methods, 2) improving calibration and validation of dynamic modelling approaches and 3) developing best-practise guidelines for applying these models. Further, more robust decision-making can be achieved by 4) combining multiple modelling approaches to assess uncertainty, and 5) placing models at the core of adaptive management. These efforts must be accompanied by long-term funding for modelling and monitoring, and improved communication between research and practise to ensure optimal conservation and restoration outcomes.}, language = {en} } @article{MalchowBocediPalmeretal.2021, author = {Malchow, Anne-Kathleen and Bocedi, Greta and Palmer, Stephen C. F. and Travis, Justin M. J. and Zurell, Damaris}, title = {RangeShiftR}, series = {Ecography : pattern and diversity in ecology / Nordic Ecologic Society Oikos}, volume = {44}, journal = {Ecography : pattern and diversity in ecology / Nordic Ecologic Society Oikos}, number = {10}, publisher = {Wiley-Blackwell}, address = {Oxford [u.a.]}, issn = {1600-0587}, doi = {10.1111/ecog.05689}, pages = {1443 -- 1452}, year = {2021}, abstract = {Reliably modelling the demographic and distributional responses of a species to environmental changes can be crucial for successful conservation and management planning. Process-based models have the potential to achieve this goal, but so far they remain underused for predictions of species' distributions. Individual-based models offer the additional capability to model inter-individual variation and evolutionary dynamics and thus capture adaptive responses to environmental change. We present RangeShiftR, an R implementation of a flexible individual-based modelling platform which simulates eco-evolutionary dynamics in a spatially explicit way. The package provides flexible and fast simulations by making the software RangeShifter available for the widely used statistical programming platform R. The package features additional auxiliary functions to support model specification and analysis of results. We provide an outline of the package's functionality, describe the underlying model structure with its main components and present a short example. RangeShiftR offers substantial model complexity, especially for the demographic and dispersal processes. It comes with elaborate tutorials and comprehensive documentation to facilitate learning the software and provide help at all levels. As the core code is implemented in C++, the computations are fast. The complete source code is published under a public licence, making adaptations and contributions feasible. The RangeShiftR package facilitates the application of individual-based and mechanistic modelling to eco-evolutionary questions by operating a flexible and powerful simulation model from R. It allows effortless interoperation with existing packages to create streamlined workflows that can include data preparation, integrated model specification and results analysis. Moreover, the implementation in R strengthens the potential for coupling RangeShiftR with other models.}, language = {en} } @article{ZurellvonWehrdenRoticsetal.2018, author = {Zurell, Damaris and von Wehrden, Henrik and Rotics, Shay and Kaatz, Michael and Gross, Helge and Schlag, Lena and Sch{\"a}fer, Merlin and Sapir, Nir and Turjeman, Sondra and Wikelski, Martin and Nathan, Ran and Jeltsch, Florian}, title = {Home range size and resource use of breeding and non-breeding white storks along a land use gradient}, series = {Frontiers in Ecology and Evolution}, volume = {6}, journal = {Frontiers in Ecology and Evolution}, publisher = {Frontiers Research Foundation}, address = {Lausanne}, issn = {2296-701X}, doi = {10.3389/fevo.2018.00079}, pages = {11}, year = {2018}, abstract = {Biotelemetry is increasingly used to study animal movement at high spatial and temporal resolution and guide conservation and resource management. Yet, limited sample sizes and variation in space and habitat use across regions and life stages may compromise robustness of behavioral analyses and subsequent conservation plans. Here, we assessed variation in (i) home range sizes, (ii) home range selection, and (iii) fine-scale resource selection of white storks across breeding status and regions and test model transferability. Three study areas were chosen within the Central German breeding grounds ranging from agricultural to fluvial and marshland. We monitored GPS-locations of 62 adult white storks equipped with solar-charged GPS/3D-acceleration (ACC) transmitters in 2013-2014. Home range sizes were estimated using minimum convex polygons. Generalized linear mixed models were used to assess home range selection and fine-scale resource selection by relating the home ranges and foraging sites to Corine habitat variables and normalized difference vegetation index in a presence/pseudo-absence design. We found strong variation in home range sizes across breeding stages with significantly larger home ranges in non-breeding compared to breeding white storks, but no variation between regions. Home range selection models had high explanatory power and well predicted overall density of Central German white stork breeding pairs. Also, they showed good transferability across regions and breeding status although variable importance varied considerably. Fine-scale resource selection models showed low explanatory power. Resource preferences differed both across breeding status and across regions, and model transferability was poor. Our results indicate that habitat selection of wild animals may vary considerably within and between populations, and is highly scale dependent. Thereby, home range scale analyses show higher robustness whereas fine-scale resource selection is not easily predictable and not transferable across life stages and regions. Such variation may compromise management decisions when based on data of limited sample size or limited regional coverage. We thus recommend home range scale analyses and sampling designs that cover diverse regional landscapes and ensure robust estimates of habitat suitability to conserve wild animal populations.}, language = {en} } @article{SchaeferMenzJeltschetal.2017, author = {Sch{\"a}fer, Merlin and Menz, Stephan and Jeltsch, Florian and Zurell, Damaris}, title = {sOAR: a tool for modelling optimal animal life-history strategies in cyclic environments}, series = {Ecography : pattern and diversity in ecology ; research papers forum}, volume = {41}, journal = {Ecography : pattern and diversity in ecology ; research papers forum}, number = {3}, publisher = {Wiley}, address = {Hoboken}, issn = {0906-7590}, doi = {10.1111/ecog.03328}, pages = {551 -- 557}, year = {2017}, abstract = {Periodic environments determine the life cycle of many animals across the globe and the timing of important life history events, such as reproduction and migration. These adaptive behavioural strategies are complex and can only be fully understood (and predicted) within the framework of natural selection in which species adopt evolutionary stable strategies. We present sOAR, a powerful and user-friendly implementation of the well-established framework of optimal annual routine modelling. It allows determining optimal animal life history strategies under cyclic environmental conditions using stochastic dynamic programming. It further includes the simulation of population dynamics under the optimal strategy. sOAR provides an important tool for theoretical studies on the behavioural and evolutionary ecology of animals. It is especially suited for studying bird migration. In particular, we integrated options to differentiate between costs of active and passive flight into the optimal annual routine modelling framework, as well as options to consider periodic wind conditions affecting flight energetics. We provide an illustrative example of sOAR where food supply in the wintering habitat of migratory birds significantly alters the optimal timing of migration. sOAR helps improving our understanding of how complex behaviours evolve and how behavioural decisions are constrained by internal and external factors experienced by the animal. Such knowledge is crucial for anticipating potential species' response to global environmental change.}, language = {en} }